MSE for 6 datasets in each setting.
nNoiseTFGrid <- c(0, ncol(X), ncol(X)*2, ncol(X)*4) # 100% to 33.3% data-generating TFs
nNoiseEdgeGrid <- c(-sum(X)/2, -sum(X)/4, 0, sum(X)*2, sum(X)*4) # -50% to +200% true links
nIter <- 6
pNoLeg <- list()
for(nn in 1:nIter){
set.seed(nn)
for(nnTF in 1:length(nNoiseTFGrid)){
nNoiseTFs <- nNoiseTFGrid[nnTF]
for(nnEdge in 1:length(nNoiseEdgeGrid)){
nNoiseEdges <- nNoiseEdgeGrid[nnEdge]
nNoiseEdges <- nNoiseEdgeGrid[nnEdge]
XTrue <- X
XNoisy <- addNoiseToGRN(X = XTrue,
nNoiseTFs = nNoiseTFs,
nNoiseEdges = nNoiseEdges,
noiseProb = 3/nrow(X))
# truth
truthNoisy <- simRes$fcAll
truthNoisy[simRes$fcAll == 1] <- FALSE
truthNoisy[simRes$fcAll != 1] <- TRUE
truthNoisy <- rbind(truthNoisy, matrix(rep(FALSE, nNoiseTFs * ncol(simRes$fcAll)),
nrow = nNoiseTFs, ncol=ncol(simRes$fcAll)))
## filter if necessary
keepGene <- rowSums(XNoisy) > 0
counts <- simRes$Y[keepGene,]
curAlpha <- alpha[keepGene,]
XNoisy <- XNoisy[keepGene,]
keepTF <- colSums(XNoisy) > 0
truthNoisy <- truthNoisy[keepTF,]
# get true alpha for noisy GRN
if(nNoiseTFs > 0){
alphaTrueNoisy <- cbind(curAlpha, XNoisy[,(ncol(X)+1):(ncol(X)+nNoiseTFs)])
} else {
alphaTrueNoisy <- curAlpha
}
XNoisy <- XNoisy[,keepTF]
alphaTrueNoisy <- alphaTrueNoisy[,keepTF]
alphaTrueNoisy[XNoisy == 0] <- 0
rownames(truthNoisy) <- colnames(XNoisy)
simEvalNoise <- evaluateSimulation_noRepressions_MSE(counts = counts,
design = design,
XNoisy = XNoisy,
simRes = simRes,
alpha = alphaTrueNoisy,
truth = truthNoisy,
alphaScale = 1,
XTrue = XTrue,
nNoiseEdges = nNoiseEdges)
simEvalNoise$nNoiseTF <- nNoiseTFGrid[nnTF]
simEvalNoise$nNoiseEdge <- nNoiseEdgeGrid[nnEdge]
simEvalNoise$dataset <- nn
mseList[[(nnTF-1)*(length(nNoiseEdgeGrid)) + nnEdge]] <- simEvalNoise
allRes <- evaluateSimulation_noRepressions_MSE(counts = counts,
design = design,
XNoisy = XNoisy,
simRes = simRes,
alpha = alphaTrueNoisy,
truth = truthNoisy,
alphaScale = 1,
XTrue = XTrue,
nNoiseEdges = nNoiseEdges,
returnMutc = TRUE)
allResList[[(nnTF-1)*(length(nNoiseEdgeGrid)) + nnEdge]] <- allRes
tfNames <- rownames(simRes$mu_tc)
sharedTF <- intersect(tfNames, rownames(allRes$allEdges$poisson))
if(nNoiseEdges > 0){
muDfTrueEdges <- data.frame(tf=sharedTF,
trueMu=c(simRes$mu_tc[sharedTF,]),
poisson=c(allRes$onlyTrueEdges$poisson[sharedTF,]),
dirMult=c(allRes$onlyTrueEdges$dirMult[sharedTF,]),
dirMult_alphaEst=c(allRes$onlyTrueEdges$dirMult_alphaEst[sharedTF,]),
poisson_lasso=c(allRes$onlyTrueEdges$poisson_lasso[sharedTF,]),
dirMult_lasso=c(allRes$onlyTrueEdges$dirMult_lasso[sharedTF,]),
dirMult_aphaEst_lasso=c(allRes$onlyTrueEdges$dirMult_lasso_alphaEst[sharedTF,]))
# ## pivot to long format
muDfLongTrueEdges <- pivot_longer(muDfTrueEdges, cols=colnames(muDfTrueEdges)[-c(1:2)],
names_to="method")
muDfLongTrueEdges$noiseTF <- nNoiseTFs
muDfLongTrueEdges$noiseEdge <- nNoiseEdges
muDfLongTrueEdges$dataset <- nn
if(nnTF==1 & nnEdge==4 & nn==1){ ## first time with false positive edges in the loops
muDfAll_trueEdges <- muDfLongTrueEdges
} else {
muDfAll_trueEdges <- rbind(muDfAll_trueEdges,muDfLongTrueEdges)
}
}
sharedTF <- intersect(tfNames, rownames(allRes$allEdges$poisson))
muDfAllEdges <- data.frame(tf=sharedTF,
trueMu=c(simRes$mu_tc[sharedTF,]),
poisson=c(allRes$allEdges$poisson[sharedTF,]),
dirMult=c(allRes$allEdges$dirMult[sharedTF,]),
dirMult_alphaEst=c(allRes$allEdges$dirMult_alphaEst[sharedTF,]),
poisson_lasso=c(allRes$allEdges$poisson_lasso[sharedTF,]),
dirMult_lasso=c(allRes$allEdges$dirMult_lasso[sharedTF,]),
dirMult_aphaEst_lasso=c(allRes$allEdges$dirMult_lasso_alphaEst[sharedTF,]))
## pivot to long format
muDfLongAllEdges <- pivot_longer(muDfAllEdges, cols=colnames(muDfAllEdges)[-c(1:2)],
names_to="method")
## add edge and TF info
muDfLongAllEdges$noiseTF <- nNoiseTFs
muDfLongAllEdges$noiseEdge <- nNoiseEdges
muDfLongAllEdges$dataset <- nn
if(nnTF==1 & nnEdge==1 & nn==1){
muDfAll_allEdges <- muDfLongAllEdges
} else {
muDfAll_allEdges <- rbind(muDfAll_allEdges,muDfLongAllEdges)
}
}
}
if(nn == 1){
mseListAll <- mseList
} else {
mseListAll <- c(mseListAll, mseList)
}
}
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 1 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 1 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 1 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 1 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 1 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 1 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 1 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 1 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 1 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 1 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 1 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 1 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 3 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 2 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 4 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
## Converged.
## Warning in dirMultEstimation2(counts = counts, X = X, U = U, alpha = alpha, :
## alpha_gt must be 0 or greater than or equal to 1. Converting 5 values to 1.
## Prior versus data weight is tuned to be 100%.
## Converged.
date <- Sys.Date()
date <- gsub(x=date, pattern="-", replacement="")
saveRDS(mseListAll, file=paste0("../objects/mseListAll",date,".rds"))
saveRDS(muDfAll_allEdges, file=paste0("../objects/muDfAll_allEdges",date,".rds"))
saveRDS(muDfAll_trueEdges, file=paste0("../objects/muDfAll_trueEdges",date,".rds"))
Graphic evaluation
Based on all edges
# muDfAll_allEdges <- readRDS("../objects/muDfAll_allEdges20230407.rds")
muDfAll_allEdges <- readRDS(paste0("../objects/muDfAll_allEdges",date,".rds"))
allMethods <- unique(muDfAll_allEdges$method)
pMethodList <- list()
pMethodMAList <- list()
for(mm in 1:length(allMethods)){
curMethod <- allMethods[mm]
curDf <- muDfAll_allEdges[muDfAll_allEdges$method == curMethod,]
pMethod <- ggplot(curDf, aes(x=trueMu, y=value, col=dataset)) +
geom_point(size=1/2) +
geom_abline(intercept=0, slope=1, col="red") +
facet_grid(noiseTF ~ noiseEdge) +
theme_classic() +
xlab("True value") +
ylab("Estimated value") +
ggtitle(curMethod) #+ xlim(c(0,8)) + ylim(c(0,8))
pMethodMA <- ggplot(curDf, aes(x=(trueMu+value)/2, y=log(value/trueMu), col=dataset)) +
geom_point(size=1/2) +
geom_abline(intercept=0, slope=0, col="red") +
facet_grid(noiseTF ~ noiseEdge) +
theme_classic() +
xlab("Mean") +
ylab("Log difference (estimated/true)") +
ggtitle(curMethod) +
ylim(c(-5,5))
pMethodList[[mm]] <- pMethod
pMethodMAList[[mm]] <- pMethodMA
}
pMethodList
## [[1]]

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##
## [[5]]

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## [[6]]

pMethodMAList
## [[1]]
## Warning: Removed 6416 rows containing missing values (`geom_point()`).

##
## [[2]]

##
## [[3]]
## Warning: Removed 7361 rows containing missing values (`geom_point()`).

##
## [[4]]
## Warning: Removed 6065 rows containing missing values (`geom_point()`).

##
## [[5]]

##
## [[6]]
## Warning: Removed 6973 rows containing missing values (`geom_point()`).

Based on only ture edges
# muDfAll_trueEdges <- readRDS("../objects/muDfAll_trueEdges20230407.rds")
muDfAll_trueEdges <- readRDS(paste0("../objects/muDfAll_trueEdges",date,".rds"))
allMethods <- unique(muDfAll_trueEdges$method)
pMethodList <- list()
pMethodMAList <- list()
for(mm in 1:length(allMethods)){
curMethod <- allMethods[mm]
curDf <- muDfAll_trueEdges[muDfAll_trueEdges$method == curMethod,]
pMethod <- ggplot(curDf, aes(x=trueMu, y=value, col=dataset)) +
geom_point(size=1/2) +
geom_abline(intercept=0, slope=1, col="red") +
facet_grid(noiseTF ~ noiseEdge) +
theme_classic() +
xlab("True value") +
ylab("Estimated value") +
ggtitle(curMethod) #+ xlim(c(0,8)) + ylim(c(0,8))
pMethodMA <- ggplot(curDf, aes(x=(trueMu+value)/2, y=log(value/trueMu), col=dataset)) +
geom_point(size=1/2) +
geom_abline(intercept=0, slope=0, col="red") +
facet_grid(noiseTF ~ noiseEdge) +
theme_classic() +
xlab("Mean") +
ylab("Log difference (estimated/true)") +
ggtitle(curMethod) +
ylim(c(-5,5))
pMethodList[[mm]] <- pMethod
pMethodMAList[[mm]] <- pMethodMA
}
pMethodList
## [[1]]

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## [[2]]

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## [[3]]

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## [[4]]

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## [[5]]

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## [[6]]

pMethodMAList
## [[1]]
## Warning: Removed 5505 rows containing missing values (`geom_point()`).

##
## [[2]]

##
## [[3]]
## Warning: Removed 6428 rows containing missing values (`geom_point()`).

##
## [[4]]
## Warning: Removed 5236 rows containing missing values (`geom_point()`).

##
## [[5]]

##
## [[6]]
## Warning: Removed 6089 rows containing missing values (`geom_point()`).

MSE
# mseListAll <- readRDS("../objects/mseListAll20230407.rds")
mseListAll <- readRDS(paste0("../objects/mseListAll",date,".rds"))
dfMSEAll <- do.call(rbind, mseListAll)
dfMSEAll$method <- factor(dfMSEAll$method, levels = c("poisson", "poisson_lasso",
"dirMult", "dirMult_lasso",
"dirMult_alphaEst", "dirMult_lasso_alphaEst"))
dfMSEAll$noiseEdges <- round(dfMSEAll$nNoiseEdge)
dfMSEAll$noiseTFs <- round(dfMSEAll$nNoiseTF)
dfMSEAll_allEdges <- dfMSEAll[dfMSEAll$onlyTrue==FALSE,]
ggplot(dfMSEAll_allEdges, aes(x=method, y=mse)) +
geom_boxplot(aes(col=method)) +
facet_wrap(.~noiseTFs * noiseEdges,
ncol = length(nNoiseEdgeGrid),
nrow = length(nNoiseTFGrid)) +
theme_bw() +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank()) +
scale_y_continuous(n.breaks=5) +
xlab("") + ylab("MSE") +
ylim(c(0,4.5)) +
geom_hline(yintercept=0, lty=2)
## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.

ggsave("../plots/mseAllSettings.pdf", width=12, height=9)
ggplot(dfMSEAll, aes(x=method, y=mse, fill=onlyTrue)) +
geom_boxplot(aes(col=method)) +
facet_wrap(.~noiseTFs * noiseEdges,
ncol = length(nNoiseEdgeGrid),
nrow = length(nNoiseTFGrid)) +
theme_bw() +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank()) +
scale_y_continuous(n.breaks=5) +
xlab("") + ylab("MSE") +
ylim(c(0,4.5)) +
geom_hline(yintercept=0, lty=2)
## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
